1. Field of the Invention
The present invention relates to computer-aided diagnosis (CAD)methods for automated detection of lung nodules in chest images and relates to U.S. Pat. Nos. 4,851,984, 4,907,156, 4,839,807, 4,918,534, 5,072,384, 5,133,020, 5,289,374, 5,319,549, 5,343,390, 5,359,513 and 5,463,345 well as pending U.S. application Ser. Nos. 08/174,175 (now U.S. Pat. No. 5,668,888), 07/915,631 (now U.S. Pat. No. 5,537,485), 08/060,531 (now U.S. Pat. No. 5,491,627), 08/235,530 (abandoned), 08/159,133 (now U.S. Pat. No. 5,638,458), 08/159,136 (abandoned), 08/158,389 (abandoned), 08/220,917 (now U.S. Pat. No. 5,881,124) and 08/428,867 (now U.S. Pat. No. 5,790,690).
2. Discussion of Background
Lung cancer is the leading cause of cancer death in men and women in the United States. It is estimated that, in 1992, there were 168,000 new cases and 146,000 deaths from this disease. The 5-year survival rate for patients with lung cancer is only about 13%. However, the 5-year survival rate can be increased to 41% if the disease is detected at a stage when nodules are small and localized. Currently, only 18% of lung cancer cases are discovered at such an early stage.
The correct detection and diagnosis of solitary, circumscribed pulmonary nodules in radiographic chest images are of great importance because many of these lesions are primary bronchogenic carcinomas, i.e., AJC (American Joint Committee on Cancer Staging) stage I lung cancers. These early primary lung cancers are often asymptomatic, but resectable. The survival rate will be improved greatly if the carcinoma is removed at this stage. Inasmuch as chest radiography is the most popular diagnostic modality for detecting lung nodules, the discovery of these nodules in a chest image is a source of major concern for patient and physician alike. Although solitary nodules discovered in radiographic surveys of the general population prove to be cancer in less than 5 per cent of cases, patients referred for lung tumor resection have a malignant nodule in approximately 40 per cent of cases. This percentage may be more than 50% for patients above the age of 50 years.
Nevertheless, the detection and diagnosis of pulmonary nodules in chest images remain one of the most difficult tasks performed by radiologists. Radiologists may fail to detect pulmonary nodules in 30% of actually positive cases. A previous study showed that 90% of peripheral lung cancers were visible in retrospect for months or even years on previous chest radiographs. (See J. R. Muhm, et al., "Lung cancer detected during a screening program using four-month radiographs," Radiology 148, 609-615 (1983).) The reasons for these false-negative diagnoses by radiologists could be the subtlety of nodules and the camouflaging effects of the normal anatomic background structures (i.e., structured noise), lack of clinical data or failure to review previous films, and/or some other subjective factors, such as distractions, subjective and varying decision criteria, and premature discontinuation of film reading after a definite finding.
Since the miss rate of detecting lung nodules by radiologists is rather high, it is expected that radiologists' performance could be improved with help from a computer-aided diagnosis (CAD) scheme. The CAD scheme is applied automatically to digitized chest radiographs, and radiologists are alerted to potential locations of nodules in the images. In this way, the CAD scheme provides a "second opinion" and leaves the final decision to the radiologists.
Several computerized methods have been developed since the 1970s by different researchers for the automated detection of lung nodules in chest images. None of these methods, however, has been applied in clinical trials, probably because of the large number of false positives generated, ranging from five to more than 10 false positives per chest image.